TensorFlow批读取图片

原创于 2019-07-25 14:42:33 发布 · 228 阅读

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本文介绍如何使用TensorFlow读取指定路径下的所有JPEG图像文件，并将这些图像转换为tf.float32数据类型，以便于进行深度学习模型训练。代码示例展示了从文件读取到图像解码及数据类型转换的完整过程。

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# coding:utf-8

from __future__ import print_function
import os
import tensorflow as tf


def TF_image_data(path_to_images):  
    """
    using tensorflow to read and store data
    """
    if not tf.gfile.Exists(path_to_images):
        print("path to images does not exist")
    else:
        #search all jpeg files
        path_img_list = files = os.listdir(path_to_images)
        #path_img_list = tf.gfile.Glob(os.path.join(path_to_images, '*.jpg'))
        print(path_img_list)
        total_img = []
        for file in path_img_list:
            print("the name of jpeg file:", file)
            img_jpg = tf.gfile.FastGFile(path_to_images +'/' +file,'rb').read() 
            img_decode = tf.image.decode_jpeg(img_jpg)
            img_data = tf.image.convert_image_dtype(img_decode, dtype = tf.float32)
            total_img.append(img_data)
        print(len(total_img))
        return total_img 


if __name__ == '__main__':
    path_to_images = './Images'
    with tf.Session() as sess:
        TF_image_data(path_to_images)